Revisiting the Miles and Snow strategic framework: uncovering interrelationships between strategic types,capabilities, environmental uncertainty,and firm performance

The Miles and Snow strategic type framework is re‐examined with respect to interrelationships with several theoretically relevant batteries of variables, including SBU strategic capabilities, environmental uncertainty, and performance. A newly developed constrained, multi‐objective, classification methodology is modified to empirically derive an alternative quantitative typology using survey data obtained from 709 firms in three countries (China, Japan, United States). We compare the Miles and Snow typology to the classification empirically derived utilizing this combinatorial optimization clustering procedure. With respect to both variable battery associations and objective statistical criteria, we show that the empirically derived solution clearly dominates the traditional P‐A‐D‐R typology of Miles and Snow. Implications and directions for future research are provided. Copyright © 2004 John Wiley & Sons, Ltd.     

Performance assessment of ensemble learning systems in financial data classification

Financial data classification plays an important role in investment and banking industry with the purpose to control default risk, improve cash and select the best customers. Ensemble learning and classification systems are becoming gradually more applied to classify financial data where outputs from different classification systems are combined. The objective of this research is to assess the relative performance of existing state‐of‐the‐art ensemble learning and classification systems with applications to corporate bankruptcy prediction and credit scoring. The considered ensemble systems include AdaBoost, LogitBoost, RUSBoost, subspace, and bagging ensemble system. The experimental results from three datasets: one is composed of quantitative attributes, one encompasses qualitative data, and another one combines both quantitative and qualitative attributes. By using ten‐fold cross‐validation method, the experimental results show that AdaBoost is effective in terms of low classification error, limited complexity, and short time processing of the data. In addition, the experimental results show that ensemble classification systems outperform existing models that were recently validated on the same databases. Therefore, ensemble classification system can be employed to increase the reliability and consistency of financial data classification task.     

The future of Russian gas exports to East Asia: Feasibility and market implications

For a long time, the Russian government has aimed to diversify gas exports to East Asian countries. This gearing of Russia towards Asia will have great consequences on world energy, the global economy, and geopolitics in the coming years. This paper analyzes the growth potential of Russia's diversification strategy and the impact this policy would have on sales to Europe. As the most likely scenario is for total gas exports to grow at a moderate rate from 2010 to 2030, any increase in sales to Asia could make difficult the raising of exports to Europe. Our thesis is that this trade-off will depend primarily on domestic consumption trends, geographic targeting of investments, and commercial and financial alliances with foreign partners. However, imports from Central Asia, declining exports to Ukraine and Belarus, and Gazprom investments in other gas-producing countries could also affect gas exports and gas distribution among different markets.     

Good news, bad news and rating announcements: An empirical investigation

In this paper we employ a new approach to test the contribution of information in rating announcements. This is the first study to test and corroborate how the CDS market responds to rating actions after controlling for the presence of concurrent public and private information. We show that since the clustering of rating announcements characterizes economically significant developments, the common practice of using “uncontaminated” samples underestimates market response. As in previous studies, we find that the market response to bad news is stronger than to good news. Nevertheless, bad news and negative rating announcements tend to cluster. Therefore, the residual contribution of negative rating announcements is small and in some cases insignificant. Positive rating announcements are less frequent and less clustered, though their residual contribution is still significant.     

P-star in times of crisis – Forecasting inflation for the euro area

In this paper we present three empirically testable versions of the common p-star model and evaluate their forecasting performance using conventional techniques. We try to answer the question if the p-star approach is preferable to achieve a reliable short-run inflation forecast and with regard to the latter we incur the need for a stable demand for money function. Our findings indicate the recurrence of the relevance of the monetary pillar of the ECB's two-pillar framework. In addition, we check for the effects of the current financial and economic crisis that started in 2007 on the forecasting performance, using two sub-sample periods, one excluding and one including the latter, and analyze the impact of the applied filter technique to compute the required equilibrium values.     

Do optimal diversification strategies outperform the 1/N strategy in U.K. stock returns?

This paper examines whether optimal diversification strategies outperform the 1/N strategy in U.K. stock returns. The study focuses on the performance of recent strategies developed by Tu and Zhou (2011) and Kirby and Ostdiek (2010). I find that a number of optimal asset allocation strategies can significantly outperform the 1/N strategy even after adjusting for trading costs. The strategies developed by Kirby and Ostdiek outperform the 1/N strategy, even at higher trading costs, due to the low turnover of these strategies. The strategies of Tu and Zhou have mixed performance after adjusting for trading costs due to the high turnover of these strategies. The results of the paper provide support for the use of optimal diversification strategies.     

Gold and the US dollar: Hedge or haven?

Using a model of dynamic conditional correlations covering 23 years of weekly data for 16 major dollar-paired exchange rates, this paper addresses a practical investment question: Does gold act as a hedge against the US dollar, as a safe haven, or neither? Key findings are as follows. (i) During the past 23 years gold has behaved as a hedge against the US dollar. (ii) Gold has been a poor safe haven. (iii) In recent years gold has acted, increasingly, as an effective hedge against currency risk associated with the US dollar.     

Exchange rate regime choice and currency crises

Exchange rate regime choice is not exogenous, but it depends on the structural, political and financial features of countries. However, it is often the case that the regime actually pursued and the one that is imposed by country features do not match one to one. The existing empirical crisis models do not take fully into account the regime in which the crisis unfolded. The aim of this paper is to incorporate the appropriateness of the regime choice into the standard currency crisis model. The results show that the odds of crisis increase significantly in countries which have chosen regimes inconsistently.     

Measuring price discovery: The variance ratio, the R, and the weighted price contribution

We analyze the statistical properties of three price discovery measures: The variance ratio, the weighted price contribution (WPC), and the R² of unbiasedness regressions. We find that, if the price process is a driftless martingale, only the WPC is an unbiased estimator for the return variance explained during a time interval. For autocorrelated processes with a drift, only the R² of the unbiasedness regression is consistent, but it is biased for small samples.